Given a real symmetric matrix S, the Schur decomposition finds the eigenvalues and eigenvectors of S. If D is the diagonal matrix formed by the eigenvalues and U the unitarian matrix of the eigenvectors we can write the Schur decomposition as S = U\cdot D \cdot U^T where {@latex$ \cdot } is the standard matrix product and {@latex$ ^T } is the transpose operator.
This class implements the Schur decomposition using the symmetric threshold Jacobi algorithm. For details on the different Jacobi transfomations. @see "Matrix computation," second edition, by Golub and Van Loan, The Johns Hopkins University Press @author Richard Gomes
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